Interfacing aptamers, nanoparticles and graphene in a hierarchical structure for highly selective detection of biomolecules in OECT devices

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Carlotta Peruzzi
Silvia Battistoni
Daniela Montesarchio
Matteo Cocuzza
Simone Luigi Marasso
Alessio Verna
Laura Pasquardini
Roberto Verucchi
Lucrezia Aversa
Victor Erokhin
Pasquale D’Angelo
Salvatore Iannotta
机构
[1] IMEM - CNR Institute of Materials for Electronics and Magnetism,Physics Department and Ph.D. School on Material Science and Technology
[2] University of Parma,Department of Chemical Sciences
[3] University of Naples “Federico II”,Chilab
[4] Politecnico di Torino, Materials and Microsystems Laboratory, DISAT
[5] University of Trento,Department of Industrial Engineering
[6] Trento Unit,IMEM
[7] Indivenire s.r.l., CNR Institute of Materials for Electronics and Magnetism
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In several biomedical applications, the detection of biomarkers demands high sensitivity, selectivity and easy-to-use devices. Organic electrochemical transistors (OECTs) represent a promising class of devices combining a minimal invasiveness and good signal transduction. However, OECTs lack of intrinsic selectivity that should be implemented by specific approaches to make them well suitable for biomedical applications. Here, we report on a biosensor in which selectivity and a high sensitivity are achieved by interfacing, in an OECT architecture, a novel gate electrode based on aptamers, Au nanoparticles and graphene hierarchically organized to optimize the final response. The fabricated biosensor performs state of the art limit of detection monitoring biomolecules, such as thrombin-with a limit of detection in the picomolar range (≤ 5 pM) and a very good selectivity even in presence of supraphysiological concentrations of Bovine Serum Albumin (BSA-1mM). These accomplishments are the final result of the gate hierarchic structure that reduces sterich indrance that could contrast the recognition events and minimizes false positive, because of the low affinity of graphene towards the physiological environment. Since our approach can be easily applied to a large variety of different biomarkers, we envisage a relevant potential for a large series of different biomedical applications.
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